Mutation analysis introduces program defects with the intend of verifying whether candidate tests are able to trigger anomalous behaviour. In case the tests can distinguish the defective behaviour from that of the original program, they are considered of good quality -otherwise developers need to design new tests. While, this method has been shown to be effective, industry-scale code challenges its applicability due to the sheer number of mutants and test executions it requires. In this paper we present PIT, a practical mutation testing tool for Java, applicable on real-world codebases. PIT is fast since it operates on bytecode and optimises mutant executions. It is also robust and well integrated with development tools, as it can be invoked through a command line interface, Ant or Maven. PIT is also open source and hence, publicly available at http://pitest.org/

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A considerable amount of energy is consumed to cool electronic equipment in data centers. A method for substantially reducing the energy needed for this cooling was demonstrated. The method involves immersing electronic equipment in a non-conductive liquid that changes phase from a liquid to a gas. The liquid used was 3M Novec 649. Two-phase immersion cooling using this liquid is not viable at this time. The primary obstacles are IT equipment failures and costs. However, the demonstrated technology met the performance objectives for energy efficiency and greenhouse gas reduction. Before commercialization of this technology can occur, a root cause analysis of the failures should be completed, and the design changes proven. We acknowledge the support of Russ Stacy (SGI) for his work on the baseline (Base Case) and pilot testing setup and data collection. In addition, thanks go to Cheng Lao also from SGI, for his guidance on the application and operation of benchmarking software. We are grateful to Xindi Cai (Schneider-Electric) for thermal controls design and programming. Many thanks to Vali Sorell (Syska Hennessy Group) and Steve Greenberg (LBNL) for technical guidance and development of simulation assumptions.

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